Handling Uncertainty in Answer Set Programming

AAAI 2015 pp. 4218-4219

doi:10.1609/AAAI.V29I1.9726 /aaai/2015/wang2015aaai-handling/

Abstract

We present a probabilistic extension of logic programs under the stable model semantics, inspired by the concept of Markov Logic Networks. The proposed language takes advantage of both formalisms in a single framework, allowing us to represent commonsense reasoning problems that require both logical and probabilistic reasoning in an intuitive and elaboration tolerant way.

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Cite

Text

Wang and Lee. "Handling Uncertainty in Answer Set Programming." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9726

Markdown

[Wang and Lee. "Handling Uncertainty in Answer Set Programming." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/wang2015aaai-handling/) doi:10.1609/AAAI.V29I1.9726

BibTeX

@inproceedings{wang2015aaai-handling,
  title     = {{Handling Uncertainty in Answer Set Programming}},
  author    = {Wang, Yi and Lee, Joohyung},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {4218-4219},
  doi       = {10.1609/AAAI.V29I1.9726},
  url       = {https://mlanthology.org/aaai/2015/wang2015aaai-handling/}
}